We consider the problem of finding a maximal matching of minimum size, given an unweighted general graph. This problem is a well studied and it is known to be NP-hard even for some restricted classes of graphs. Moreover, in case of general graphs, it is NP-hard to approximate the Minimum Maximal Matching (shortly MMM) within any constant factor smaller than 7/6. The current best known approximation algorithm is the straightforward algorithm which yields an approximation ratio of 2. We propose the first nontrivial algorithm yields an approximation ratio of 2-c(log n/n), for an arbitrarily positive constant c. Our algorithm is based on the local search technique and utilizes an approximate solution of the Minimum Weighted Maximal Matching problem in order to achieve the desirable approximation ratio.
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机译:考虑到一个未加权的一般图,我们考虑找到最小尺寸的最大匹配的问题。这个问题是一个很好的研究,即使对于一些限制的图表,也是难以努力的。此外,在一般图的情况下,它是NP - 难以近似于小于7/6的任何恒定因子内的最小最大匹配(短mmm)。当前最着名的近似算法是直接算法,其产生近似比为2.我们提出了任意正常数C的近似算法的近似比为2-C(log n / n)。我们的算法基于本地搜索技术,利用最小加权最大匹配问题的近似解,以实现所需的近似比。
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